Contents

Big picture

Time period

Development summary

2010 – 2014

DeepMind initiates as a British AI startup. Before being acquired by Google, it remains relatively unknown.[1]

2014 <

Google's DeepMind era. The acquired company starts being known worldwide. Since being acquired by Google, DeepMind's AI would be used to beat humans at board games and create free apps with the British National Health Service. Neither application would make profit for Google so far.[2]

2016 <

DeepMind becomes renowned after its AlphaGo program beats a human professional Go player for the first time and again when AlphaGo beats Lee Sedol, the world champion, in a five-game match.[3]

Present time

DeepMind is considered today one of the leading AI companies in the world. It has a team of around 700 people, with most of those based out of Google's headquarters in King's Cross, London.[4]

DeepMind reveals having developed an AI algorithm able to learn how to play iconic early video games like Breakout and Pong simply by watching them being played on a vintage 1977 Atari 2600 games console. Having surmised the rules and rewards from the way the pixels were batted about the screen, the algorithm is then able to beat human opponents at playing the games.[11]

DeepMind unveils a neural network that can access an external memory like a conventional Turing machine. The project mimics properties of the human brain's short-term working memory. The result is a computer able to mimic some of the brain’s memory skills and even program like a human.[14][15][16][17]

Mustafa Suleyman describes DeepMind's work during a machine learning conference in London: "Our deep learning tool has now been deployed in many environments, particularly across Google in many of our production systems."[6]

2015

September

Partnership

DeepMind partners with the Royal Free NHS Trust to develop a patient safety app called Streams, aimed at reviewing test results for signs of sickness and sending staff instant alerts if an urgent assessment is required. The app would also help clinicians to quickly check for other serious conditions such as acute kidney injury and display results of blood tests, scans, and x-rays at the touch of a button.[6][19]

DeepMind builds an artificial intelligence agent that can learn to successfully play 49 classic Atari games by itself, with minimal input. The researchers claim software that learns to play video games could graduate to the real world before long.[22][23][24][25]

2016

February

Partnership

DeepMind announces that it is teaming with the National Health Service to build an app called Streams to help hospital staff monitor patients with kidney disease.[26]

2016

February 24

Team

DeepMind launches a new division called DeepMind Health, an initiative aimed at creating apps for medical professionals that can help identify patients at risk of complications.[27][28][29][30]

2016

April

Controversy

New Scientist obtains a copy of a data-sharing agreement between DeepMind and the Royal Free London NHS Foundation Trust. The latter operates three London hospitals where an estimated 1.6 million patients are treated annually. The agreement shows DeepMind Health had access to admissions, discharge and transfer data, accident and emergency, pathology and radiology, and critical care at these hospitals, including personal details such as whether patients have been diagnosed with HIV, suffered from depression or have ever undergone an abortion in order to conduct research to seek better outcomes in various health conditions.[31][32]

DeepMind develops a ‘big red button’ to stop AIs from causing harm, using a framework in the form of "safely interruptible" artificial intelligence. The system guarantees that a machine will not learn to resist attempts by humans to intervene in its learning processes.[33][34][35]

DeepMind claims having significantly improved computer-generated speech with its new system called WaveNet, an AI technology making machines sound more like humans. The system generates voices by sampling real human speech and directly modeling audio waveforms based on it, as well as its previously generated audio.[42][43][44][45]

DeepMind unveils an AI “working memory” able to learn how to solve tasks for itself, such as how best to get from A to B on the London tube network. The AI combines both data processing with self-learning code. The new algorithm is able to retain information in its memory and use its learnings to solve problems in some areas.[46][47][48]

2016

November 4

Partnership

DeepMind teams with Blizzard Entertainment to release an open test environment within the StarCraft II game for artificial intelligence researchers to use worldwide. DeepMind would use deep reinforcement learning to develop an AI agent that can play StarCraft II effectively.[49][50][51]

2016

November 22

Partnership

DeepMind announces a five-year agreement with a UK National Health Service trust that would give it access to patient data to develop and deploy its healthcare app, Streams. The agreement lasts until at least 2021.[52][53][54]

2016

December 5

Userbase

DeepMind announces open-sourcing DeepMind Lab, its 3D game-like platform for agent-based AI research, so that others can try and make advances in the field of AI. The DeepMind Lab project was used to create enviroments capable of testing AI systems’ ability to achieve goals in a wide range of environments. Tasks such as navigation in mazes, collecting fruit, traversing dangerous passages, laser tag and interaction with bots have been developed to refine the programs. The development of mazes and challenges were designed using video game Quake III Arena’s 17-year-old software, to teach its artificial intelligence programs how to operate in 3D spaces.[55][56][57][58]

2017

January

Collaboration

DeepMind's experts pledge to pass on their knowledge to students enrolled on machine learning master's programs at University College London.[59]

DeepMind announces development of a new way to protect confidential health data from itself, in an attempt to assure hospitals, and the public at large, that patient confidentiality isn’t compromised as DeepMind processes the sensitive medical health records entrusted to it.[60][61]

DeepMind develops algorithms that can anticipate energy demand and supply, with the potential to cut the United Kingdom energy consumption by up to 10%.[62][63][64][65]

2017

April 17

Userbase

DeepMind open sources TensorFlow library Sonnet, its object-oriented neural network library. Sonnet is a higher-level library that meshes well with DeepMind’s internal best-practices for research.[66][67]

2017

May

Controversy

Sky News publishes a leaked letter from the National Data Guardian, Dame Fiona Caldicott, revealing that in her "considered opinion" the data-sharing agreement between DeepMind and the Royal Free took place on an "inappropriate legal basis".[68]

DeepMind uses reinforcement learning to master parkour, using a virtual course designed by the researchers which features drops, hurdles, and ledges. All of the navigation is self-taught by the AI using a trial-and-error approach to working out how to move forward and progress across the course as fast as possible.[73][74]

DeepMind releases a paper describing new developments for "imagination-based planning" to AI and algorithms that simulate the human ability to construct plans. The AI can reason through decisions and make plans for the future, without being bound by human instructions.[75][76][77][78]

2017

October 4

Team

DeepMind launches DeepMind Ethics & Society (DMES), a new research group recruiting advisers from academia and charity sector with the purpose to ‘help technologists put ethics into practice’ and help coping with artificial intelligence to consider the “real-world impacts” of replicating human intelligence. The group consists of six independent research fellows, eight full-time researchers, and nine partnerships with other research institutions. It would explore topics such as algorithmic bias, accountability, and autonomous killing machines.[79][80][81]

DeepMind announces that it is teaming with the U.S. Department of Veterans Affairs in an attempt to use machine learning to predict the onset of acute kidney injury in patients, and also more broadly the general deterioration of patients during a hospital stay so that doctors and nurses can more quickly treat patients in need.[91]

DeepMind develops a neural network that teaches itself to ‘imagine’ a scene from different viewpoints, based on just a single image. The new type of computer vision algorithm can generate 3D models of a scene from 2D snapshots. It can tease out details from the static images to guess at spatial relationships, including the camera’s position. Dubbed a Generative Query Network (GQN), the system gets rid of labels and focuses on what's known as unsupervised learning.[98][99][100][101]

2018

June 15

Controversy

The DeepMind Health Independent Reviewers’ 2018 report warns on the potential for DeepMind Health to be able to “exert excessive monopoly power” as a result of the data access and streaming infrastructure that’s bundled with provision of the Streams app, which would position DeepMind as the access-controlling intermediary between the structured health data and any other third parties.[102][103]

DeepMind, along with tech leaders, including Elon Musk, sign a pledge promising to not develop “lethal autonomous weapons.” They also call on governments to institute laws against such technology. The pledge is organized by the Future of Life Institute, an outreach geroup focused on tackling existential risks.[109][110][111]

DeepMind announces partnership with Unity Technologies with the purpose to accelerate machine learning and artificial intelligence research. The new collaboration would focus on "virtual environments" that DeepMind can use to test and visualize experimental algorithms.[116][117][118][119]

DeepMind furthers cancer research and announces having been given access to mammograms from roughly 30,000 women that were taken at Jikei University Hospital in Tokyo, Japan between 2007 and 2018. The data would be used to refine DeepMind's AI breast cancer detection algorithms.[120][121]

2018

November 13

Team

As part of a reorganization of its health care efforts, DeepMind announces that its health division and the Streams app would be absorbed into Google Health.[122][123]

DeepMind unveils AlphaFold, an algorithm able to predict the complex, three-dimensional shapes into which proteins can be folded. The prediction is based solely on their genetic sequence.[124][125][126][127]

DeepMind develops algorithm aimed at boosting wind energy efficiency. Google reports having increased energy production by 20% after installing its own AI software across its largest renewable energy facilities in the United States.[132][133]

2019

April

Team

Google disbands advisory board for DeepMind Health. It is the second disbanded review panel related to Alphabet's AI dealings.[134][135][136]

DeepMind researchers develop an AI tasked with teaching itself to solve arithmetic, algebra and probability problems, among others. However, the neural network performs poorly when tested on a maths exam taken by 16-year-olds in the United Kingdom, getting just 14 out of 40 questions correct, or the equivalent of an E grade.[137][138]